---
id: "framework-ai-skill-hierarchy"
type: "framework"
source_timestamps: ["00:02:32", "00:02:40"]
tags: ["skill-development", "mental-models"]
related: ["concept-specification-engineering", "concept-context-engineering"]
steps_count: 4
sources: ["s22-saas-replacement"]
sourceVaultSlug: "s22-saas-replacement"
originDay: 22
---
# The AI Skill Hierarchy

## Summary

A four-tier hierarchy describing the evolution of skills required to effectively use AI, moving from basic interaction to advanced, agentic collaboration.

## The Four Tiers (bottom → top)

1. **Prompt Craft** — The foundational layer of basic interaction and phrasing. Knowing how to ask.
2. **Context Engineering** — Building the *infrastructure* (notably the [[concept-open-brain-d22]]) that automatically supplies the AI with the necessary background information. This is where memory architecture lives.
3. **Intent Engineering** — The strategic alignment of the AI's goals with the user's broader objectives. Why are we doing this at all?
4. **Specification Engineering** — The apex skill: precisely defining constraints and requirements for the task at hand, *relying on the lower tiers to handle context*. See [[concept-specification-engineering]].

## How to Use This Framework

- Diagnose where your current AI workflow tops out. Most users are stuck at Prompt Craft.
- Recognize that you cannot leapfrog: weak Context Engineering ceilings out Specification Engineering. This is why an Open Brain unlocks the apex skill.
- Investments compound *upward*: better memory infrastructure yields better specs yield better agent autonomy.

## Cross-References

- The CEO of Shopify, [[entity-toby-lutke-d22]], frames human organizational dysfunction as 'bad human context engineering' — the same framework applied to humans.
- The hierarchy underwrites [[claim-architecture-over-models]].


## Related across days
- [[framework-four-layers-context]]
- [[framework-intent-gap-layers]]
- [[concept-spec-quality-bottleneck]]